How to Perfect the Customer Service Journey with AI

Summary

During this webinar, Peter Johnson (VP of Product) and Vikas Bhambri (SVP of Sales and Client Services) discuss the ways in which AI can improve the customer service experience. They highlight the expected 143% growth in AI usage over the next few years and the importance of integrating it seamlessly into existing support processes. In addition, the discussion focuses on how AI can be used to intelligently route inquiries, improve agent efficiency, and enhance overall customer satisfaction. The ultimate goal is to optimize support, increase satisfaction, and streamline interactions between customers and agents through AI-powered solutions.

Key Takeaways

1. AI’s Growing Significance in Customer Service: The webinar highlights the projected 143% growth of AI in customer service, emphasizing its increasing importance for businesses to stay competitive and provide efficient support.
2. Seamless Integration for Enhanced Support: Peter Johnson and Vikas Bhambri stress the need for seamlessly integrating AI into existing customer support processes to ensure a smooth and effective customer experience.
3. Balancing Self-Service and Human Interaction: While customers prefer self-service for simple queries, it is crucial to offer the option of escalating to human agents when needed, striking the right balance between automation and personal touch.
4. Leveraging AI for Intelligent Routing: The discussion revolves around using AI to intelligently route inquiries, ensuring customers are matched with the right agents, leading to quicker and more satisfactory resolutions.
5. Empowering Agents with AI-Driven Tools: AI can empower agents with contextual information, action shortcuts, and training improvements, enabling them to provide more efficient and effective support, leading to improved customer satisfaction.

Transcript

Alright. Welcome everybody to today’s webinar. We’re excited to get going today. We’re gonna be talking about how to perfect the customer service journey with artificial intelligence And to do that, we brought on a couple special guests.

Peter Johnson, who’s currently our VP of Product and Bicus Bombre, our SVP of Sales and client services. So P. J. Vocus, thanks for joining.

How are you guys doing? Good. Thanks for having us, Gabe. Awesome. Awesome. Well, before we do, a couple of house clipkeeping items, for the audience, you will have this recording.

If you gotta jump off a little bit early, we’ll make it available.

Number two, I want you to open up your chat. We want this to be interactive. We got a lot of customers, a lot of prospects who are, thinking about artificial intelligence today, but I want your questions and comments to come in. So if you can, open up that little widget chat and put your name and where you’re from. I want you to get used to using that as we go through today’s talk track. And while we do that, PG, can you just take a few seconds and tell us just a little bit more about what you do here at customer?

Sure.

So on the VP of product And I work with the product managers and our squads to figure out what are the most important features we could be developing for our customers based off of what we’re hearing. From our customers or from the market, and then we build those features, release them and get feedback on them. So the roadmap and then the actual poor customer functionality is part of my team is that that owns that. Love it.

Alright. And Vicus, why don’t you take a minute and, do the same? Sure. Vicus, Bambry, responsible for sales and customer experience here, customer, which includes professional services, customer success, and support organizations.

And, you know, my chief responsibility is breaking, bringing the great product that PJ and his team build, to market Love it. Love it. So let’s dive in you guys. I wanna start a big picture, just with a couple of stats about AI, and get your quick take on this.

One hundred and forty-three percent growth in, particularly in customer service over the next couple, years. And then lot of differentiation between companies thinking about using AI and not using AI. Market has changed. We’re in a different world.

How do you guys see the current market and AI kinda coming together? And again, looking for more of that hundred thousand foot view, Vicus, maybe we can start with you. Sure. You know, look, this doesn’t surprise me, right?

At the end of the day, AI is a very hot buzzword in technology regardless of the subject area. So why would customer service be different?

So I think it is definitely if I, you know, for most of the customer service leaders that, you know, I speak to. It’s a top-three initiative, within the next twelve to eighteen months. So it’s definitely on the, you know, it’s it’s on the radar.

Concern I have is that most people when you then double click and say, well, what does that mean?

That’s when it kind of there’s a big drop off. Right? It’s like we all know the word. Right?

We’ve all heard the word a. No. We just don’t know what to do with it. Right.

It’s all about, to add on to that because it’s all about the actual applications that enable your business to be better or more efficient. Ultimately. Right? And we’re gonna talk about a lot of those applications today, but, ultimately, it’s around being able to handle scale. And specific to your question, Gabe, I think, in today’s climate, and I mean, like, you know, this new COVID world, I think we’re seeing two things happen. Some companies are getting bombarded with customer support requests, and they have huge scale up scale that Unfortunately, traditional bit products make it so that they have to scale the number of agents that they have at the same time.

And AI can help with that. Ultimately, and being able to handle those waves better. And then there’s there’s companies that are lowering their volume or unfortunately having the furlough employees and things like that. And the AI in that situation can make those agents maybe that are smaller teams, but still have high volumes of support or requests, still be able to provide the same caliber of customer support.

Yeah. I like that. And I think that’s where we need to try to go today We need to kind of boil it down rather than just saying AI is important. Go do it.

Go get it. It’s kinda like let’s let you know, let’s break it down. Let’s talk about the customer journey that we all are familiar with. And then let’s see if we can figure out how AI can play a role in that.

And because I love the way you kind of sketch this when we’re thinking about it. Can you take us through your ideas on the customer journey and where you see AI kind of playing a role? Sure. And just to kind of, you know, tap into what you just mentioned, right, is my big concern when I, when I, you know, I’m even having conversations with customers and prospects about eye is what kind is in the back of my head is kind of the way chat was referenced in the customer service space, you know, five, seven years ago.

People were like, well, we have to do chat.

Okay. Why? And then they blocked it on their website, and they’re like, well, nobody’s chatting with us. We gotta turn it off because obviously, you know, and so there wasn’t really a lot of thought that goes in.

So I think with AI, the way I look at it is AI needs to blend it seamlessly into what you today. And that means the agent experience has to be part of the conversation. Right? So the primary use case where a lot of people are starting their AI journey, you know, you know, as PJ was saying, is with self-service.

How do we make customers, capable of handling, you know, inquiries themselves or tickets themselves So they don’t have to work with a human agent. And, you know, in particular in the midst of this crisis, so many people are seeing this surge of inquiries, people are really aware, of what they need to do there. So first kind of step is how do we allow the customer to self-serve? But reality is the customer is not always gonna be able to self serve.

And this is where that seamless integration to the human agent comes in place, which is How do you then route, and use intelligence to route that inquiry if you are going to pass it on to human agent? And then when it does get to a human agent, how do you make that agent even more effective using intelligence or artificial intelligence to generate recommendations and solutions for them. So those are kind of the three key parts of the customer journey that all need to have a strong foundation underneath them because, you know, otherwise, you’re going to do very simplistic or foolish things in that customer journey where you’re actually gonna see a a drop off or negative CSAT because, you know, customers or your agents are gonna be come, frustrated with that experience.

Yeah. This is this is good. We actually had two questions that come in. In PJ, you might wanna pipe in here as well.

One’s from Beth and Tom. The first one from Beth was just on the self-service. Do you guys have an opinion? Are customers embracing, working with, you know, quote-unquote deflection type functionalities?

Or are they actually kind of like put off by it? Thoughts on that. Man, Gabe, if you go to that next slide, it’ll it might give you a a little, little insight there. Oh, Look at that. Is that true?

Oh, yeah. I mean, so so he I just I didn’t know that. I thought it was honestly not planned. I promised I was not planned.

But thank you Beth for, for reaching. No. Thank you, Beth. I mean, you know, so here’s the thing.

Right? I mean, for a long time, people were of the debate, that, you know, you know, self-service and some companies use the term deflection. It has a kind of a negative connotation. I mean, it does.

It does. I don’t wanna talk to to my customer, but the reality is — Yeah. — the customer want.

And customers are increasingly telling brands, we don’t wanna talk to you about things that we should be able to take care of ourselves. Right? I mean, The quick example I often use, look, if I’m booking a round-trip ticket from New York to LA, right? I wanna go to a website I wanna go to a mobile app.

That’s self-service, and I wanna be able to book a round-trip ticket without ever speaking to a human being. Right? Now if there’s an issue, if I wanna do a complex journey, maybe I, you know, I’m going, you know, Florida to LA to Seattle back to New York. Maybe I wanna speak to you and being But we’re seeing this, you know, be more and more than norm, from a customer perspective.

Yeah, Pijer, you wanna Yeah. I I think ultimately our product mission too, and any customer support organization’s mission is to give your customers the right resolution as quickly as possible. Right? That right part depends on the quality of your content, or even if, say, so so called traditional deflection can actually, actually solve that customer problem.

You may have some more, complex answer that you need to have solved or an action, like a return or a reset or refund or something. So oftentimes traditional knowledge-based functionality can’t always do that. So, but you as a customer are you’re you’re generally looking for speed and less back and forth. Right?

Nobody wants to wait on a phone and have to, like, dial through the IVRs and things. That’s where I think that self-service use cases that it helps out for people that are trying to get their answers solved by an article. But if you got something more complex, like an order. Unfortunately, they traditionally are leaving a lot short a little bit right now in terms of customer experience.

Yeah. Guys, these are such good questions coming in. Please do keep them coming, and I wanna address a couple of them here, and then we can dive in deeper. So Tom did ask something just about routing.

He basically said right now my team is just all accessing an email queue to, you know, and working through that and he adds a little more detail here.

How should you route and tell, like, what what what is best practice to route intelligently? And we’re gonna get into that more, but quick thoughts on that because I don’t wanna leave Tom hanging Yeah. I’ll I’ll take a first pass. I mean, so so if you look at it, you know, obviously go grabbing inquiries that come in out of a kind of a dynamic list is is one approach.

What you see, you know, even a traditional contact center often works in a first in first out. Right? So an inquiry comes in we route it to the first available agent, or representative, and we have them resolve it. And then of course once they resolve it, they get the next one and the next one. So kind of a push model, in terms of pushing those inquiries.

People have gotten obviously a bit smarter over time and are taking inputs. If you if you look if anybody on on the webinar has actually ever reached out to any brand via an IVR or phone call. Right? You punch in some basic data they figure out a little bit about who you are and then they route you. Maybe you’re a platinum customer versus a standard customer. Right?

And now even taking it further, and we’ll talk a bit more about this. How do you take that intelligence that you have about the customer actually the state of their being in that moment. What I mean by that is something as interesting as do they have an order that’s out for delivery versus one that’s been delivered and use that data to route them to the right team with a route eight, right, agent. So lot of different ways you can kinda matrix how you wanna route your customers to, to the right individuals. That’s a good one. PJ, would you add anything before we kinda jump a little more into self-missing a couple more of these questions?

No. I I I I think it’s I’d like to address these kinds of one in a piece and talk about what I see some people asking what we’re doing in some of those use cases so we can get into those. Yeah. Let let let’s do that.

So, Vic, you were kinda setting up any last pieces on kind of the self-service piece before we dive in to kinda how we’re thinking about solving that? Yeah. Look, I think a lot of a lot of brands have put in what I would say is V zero of the self-service strategy, which is knowledge base or an FAQ, right? I I don’t think there’s a brand whose website I wouldn’t go to today.

That doesn’t have one, right?

You know, whether they’re a mature brand or one that I just spun up yesterday. So I think everybody’s got that. Now the the key piece is how do we intelligently deliver that information to the customer based on their inquiry and what they’re trying to solve for at that time. And so that’s now where it’s kind of you know, further maturity of that self-service model is to take our intelligence about who that customer is what issues have, people inquired about previously, what resolutions have worked, and then serving up instead of the right agent at the right time, the right article or artifact or solution at the right time.

Interesting interesting. So I liked this summary here. So you guys talked on the right now, we’re seeing a lot of tickets increased. Right?

Certainly costs more than ever, probably.

Our hitting team’s bottom line top line.

Let’s talk solutions for a minute and how customers thinking about addressing that, P. J. Can you kinda summarize then give us a sneak peek and then we’ll get to some of these questions coming into the queue.

Sure. So the most basic format, which exists out there today and partners and things that we’ve rolled out recently with our initial customer IQ functionality is about that p zero use case, enabling customers to be able to help themselves. So we have, obviously, help article system You can create content on your web page, allow your customers to search and find that.

However, we’re also adding functionality that enables your customers who contact live channels to be able to be shown, again, conversation deflection shown some potential articles that match their question, to be able to then see that. And still, if they need to, they can still escalate to a human being if if they want to. That’s that’s really important here.

But for a lot of customers, you know, we’re seeing large percentages of initial inbound conversations being able to be deflected from, say, standard help articles.

So there’s a few things. We’re gonna we’re gonna go through this, and some of these screenshots next, Gabe. Do you mind clicking on this. So so aside from our existing knowledge based product, these are the live channels that are important.

A lot of people think about bots and chat only, but there’s still very large volume of support across email and across other things like help center forms. So On the left, this is the feature that we just rolled out, which is the ability to add a deflection inside of our conversation flow that uses this AI to suggest, here are some articles to that customer based off what their query was and what other articles have helped people in the past. Email, knowledge base, do the same thing. We’re, again, we’re building out ways to be able to use this rich data that we have in our in our platform to make accurate suggestions to customers so that it can solve their problems in omni channel fashion.

Do the next slide, please. Yep. What what what what the key though in my mind that is gonna be able to differentiate us from platform from a platform standpoint, is the fact that we are a data repository of more than just tickets or help articles.

We have things like customer’s orders.

Whatever products and services they provide, we have that in our system of record. And usually, customers that have that are contacting support about orders, if they need an exchange or a refund, I can’t do that necessarily just by reading a help article. I need maybe a person to help me or some sort of action or something like that. So if you go to the next slide, this is what we’re working on right now that we’re excited about which is being able to integrate that ordered data that we already have in our system, many of these people who are on this webinar, I believe our existing customers that have been giving us things like the products that they provide or orders and things like that and allow your customers to be able to, you know, If it’s about an order, they can click on which order, and they can see data about that order.

The traditional Wizmo flow, that’s that’s the case for e retailers. But There’s still any vertical. It’s very common for companies to field questions about their orders and have to take action. So And in terms of a deflection strategy for that, that data is really key to combine with allowing your customers to help themselves in that regard.

So, that’s important. I love that. Couple things to follow-up, and there’s a couple questions, PJ while we’re on this. So one is I love that you brought in that deflect isn’t just in chat because I’m seeing some people throwing in some questions.

Like, I think that’s where most people go, but you can deflect in other ways. I’m I’m glad we hit on that. I think that’s very important. Couple things on the chat.

One is someone noticed we kind of put like the customer icon and we called it customer up here. Do you have a best practice on should you call it a bot? You know, some people like to call it and, you know, marry, like give it a human name, Have you seen or experienced anything on kind of interacting with this chat program or profile? Yeah.

So we allow you to customize the eye on the name and all the colors of this entire widget. In fact, we’ve seen kind of split between companies that want to have it.

Well, traditionally, I’ve seen companies try not to disguise it as a person.

That’s that’s really important. You can still give it a name and to match your brand as important. But ultimately, can set the wrong expectations if they think that this is a human being typing really quickly. I think, you can lose a level of trust with your customers when you try to do that. That doesn’t mean that an inanimate object or a bot can’t have a name associated with it. So, ultimately, it’s about for us. We want our versus to define their brand experiences and the colors and content and the terminology.

I love that. Vocus, anything you’d add on that or Look, I think it’s, you know, brand authenticity is very important. Yeah. Yeah. And as you can see, you know, in our customer one, we actually introduce ourselves as Kusti, which obviously there’s not a human being named Kusti. It’s actually the name of our mascot.

Answers custody at your service. And then, of course, once the customer if the customer identifies that they can’t solve their issue themselves, And then they say I wanna, you know, I can’t solve my issue. I wanna speak to a human agent, and they hit that request. Then, of course, our our our support team introduces themselves. So I think it is important.

Authentic to be, yeah, true to your brand. Yeah. I like that. I like that. One other question, PJ, that I think is directed at you. And then let’s go to to kind of the routing.

Joe had asked this. He just said, Hey, I’m really interested in trying to figure out how to add, self-service slash deflection into kind of our current operation.

It’s a lot of different players out there. What how does customer differentiate than some of the other, you know, quote-unquote self-service or deflection type tools out there. Anything you’d highlight briefly on that? And certainly, Joe, we can do a follow-up as needed. But Yeah. Well, we’re, you know, we released so so we announced customer IQ.

I believe at the end of of last year twenty nineteen. And, we released it finally this month, and our and we’re adding a bunch of functionality to this that’s gonna be releasing over the course of the next few weeks. In fact, so If you go back to that slide, like, to the to that list of one more left, the feature on the far left try one more. It gave you mind going back to the previous one.

Yep. Yep. So the teacher in the far left of lab today, email deflection, I think, goes out tomorrow, which is great. Knowledge-based form deflection is out, and we’re adding another knowledge base form deflection feature, which is which is going out a little bit later next week.

And then if you slide two ahead — k. — we are also releasing we’ve released reporting for our deflection, which is super important.

You need to be able to understand what type of questions your customers are searching, whether or not you actually have content that matches those questions, And what is the rate? How much of your customer’s time are you saving? And how much of your business’s time? Are are you saving?

How many teammates of your or your of your agents are you saving and dust and also your customers. Right? So, so so reporting is also extremely important. So we are adding, new channels.

And from a different instance, if we were adding a bunch of different channels in terms of collection, and then What we’re adding very soon coming up is the ability to integrate your order and CRM data with, with the gut bot in that bot flow. There’s a lot of stuff coming up soon. We’re excited and rolling out kind of over the next few weeks.

K. Great. Let’s continue guys. Let’s go into route intelligence biggest back to you. Maybe you can kinda reframe this one and then let’s dive into problems and solutions.

Sure. I mean, this goes back to, I think the, you know, the question that came in early Right? So now the customer has been trying to self-serve and resolve their issue themselves and in some cases they can. Right?

And now they want to then engage a human agent. How do we, when we talk about intelligent routing, it’s all about, you know, pairing that customer up with the right agent. So what are the things that we can look at? Right?

Because ultimately our goal is to get them in the hands of the right person So you don’t hit this number, right? That customers actually are able to resolve their inquiry in that first contact resolution. So that’s why that pairing becomes so important, right? And you know, there is, you know, especially as companies are rolling out their bots, we see things where, you know, people get frustrated.

And, you know, if if and and you see this in some experiences, unfortunately, I I saw this on on a website recently where you went through the entire exchange with the bot.

And ultimately, when you couldn’t answer your inquiry, there was There was nothing. It was basically just dead like sorry can’t help you. That’s like the worst right now. Most people are not that bad or most brands aren’t that that bad at the very minimum, they will then escalate you to a human agent who will see the history of that interaction. Right?

But that’s not enough, right? Just seeing that history.

It’s taking some of that history and that relevance and any other data points about that customer and then using that to route that inquiry, to the right agent. So that’s what we think of and there’s a lot of really powerful ways that you can do that to, and, you know, I’ll let PJ talk to that. But how you, you know, once that kind of you hit that wall, is how do we make sure that the customer continues to have a seamless journey? No.

I like that framing. Yeah. PJ, let’s talk about solution. How do we kinda think about solving some of those problem?

Oh, PJ, I think you’re on mute. Did you mute yourself? Sorry. Yeah. I did. I made it for my phone. My my bad.

So so I got too excited to talk about this stuff and I forgot to look down at my phone.

So so so in in the initial, the demos that we were or screenshots we were showing before you know, ultimately routing is about connecting the person with their problem to the best suited individual on the business who’s gonna be able to address their problem. Right? And whether that’s speaking the same language of them or being able to understand what their question is about and matching it to the specialty on their team, knowing the level of frustration or urgency like Viggas is talking about and being able to to address that So all of that is being able to map your routing logic to be able to map to what your customers complaints or needs are.

So there’s a few things that we support that make this really easy and awesome. So to a few customer features sentiment analysis and language detection are actually on a free version of customer IQ, along with that basic bot chat bot that I showed before, So there’s a bunch of stuff that customers get out of the box. Sensimate analysis is every message that comes in. We detect the level of frustration on that message.

Based off of that information, not only can we route to a given team if there’s a very high level of frustration if we wanted to, but also providing quality support in a digital interface, right, a support agent sitting in a room potentially by themselves now, especially in this new day and age. And communicating via text on a screen, it’s important to try to recreate as much as possible that that interaction between two people when they’re facing each other in real life. And to me, that’s about empathy. Providing quality support is about empathy.

So not only do we advise route routing logic based off of that information, We also show that to a agent while they’re talking to somebody so that they can, you know, treat this person as if they’re a real life individual because you lose a little bit of, like, you know, tone and gestures and body language. And so we wanna try to bring that back to be able to provide and and understand frustration levels for agents. Language detection is super key from a routing standpoint. I mean, many brands supporting customers doesn’t even have to be in multiple countries.

It could be inside of the same country. You wanna be able to support multiple languages, and map those customers. So we do language detection which allows you to, take any channel, whether, like, for example, chat, sometimes you know what the browser language somebody’s in, but email, you have no idea what the block of language is. So we can take that.

And then based off the most confident language that’s returned, automatically set that language property, and then routing can take that and send it to the team that speaks that language.

And then really, lastly, classification. Here. This is really cool.

And this is something that’s gonna exist.

It’s it’s releasing the end of this month’s thirtieth and is part of the paid customer IQ tier. Ultimately categorization of conversation depends on each business, on a business-to-business basis. How, retail or categorizes their conversations totally different than how a b to b company or maybe a ride-sharing company, delivery company, all their categorization is totally different. Right? So there’s no out-of-the-box routing system that you’re gonna be able to build.

It’s it’s all totally dynamic.

So what we’re doing is we’re allowing you to use your existing data of categorizations. So let’s say you’ve already categorized a thousand conversations that, okay, well, this question was about orders. This one was about returns. This one was about buyer marketplace, seller marketplace, and that historical data, you can define that data we’ll use that to build a training model, which will automatically in real-time set that property on the conversation. So for your business, if it’s if let’s say you’re a buyer. So we have a customer, who is a two-way marketplace that is using this in beta today. And so the questions that come in through email are about buyer buyer platform or seller platform.

Our ML model automatically categorizes that say, okay. Well, this question is very similar to the buyer questions that have already been asked. So we stamp the buyer tag on it, and then that gets routed to their buyer’s teams who are specialized in buyer questions. And, again, that’s about matching the customer to the right person inside of that business.

In this case, this is using a really complex technology, machine learning, But the idea is is meant to be is communicating the simple way. It’s ultimately about providing better customer support and faster less transfers or back and forth for the end customer and less time for the business spent having to have humans hours or minutes talking to customers. I like that. I like that.

One question just came in from Spencer. He just said, when you like think about sentiment analysis, how does that What what’s the quick double click? I think he’s trying to kinda say here, like, how does it actually determine if someone is quote-unquote happier, sad? Sure.

So so the sentiment engine actually looks at the keywords, that come in. Obviously, you know, I can use an example where somebody says, hey, I’m really frustrated that obviously pretty easy, right? But it actually looks at keywords, the combination of words, the phrasing, and then uses it to assign it a score.

So that’s what the sentiment engine does. I think the other couple key things there, right, is as the conversation goes back and forth between the custom party agent. We’re also tracking the sentiment of those follow on. So it’s not just the initial, item.

So we and then we can track it for the what we call the conversations as the messages go back and forth over the lifetime of that brand’s relationship with that customer. So there’s a lot of really powerful things. In fact, One of our customers is doing something really interesting, which if you look at customer satisfaction, which is a very, foundational element of any customer service program, CSAT scores. What they’re looking at is, look, it’s great that you got a CSAT score of five if the customer came in and was happy.

Like, Okay. Right. Okay. And what you’re really looking at, customer came in frustrated, and then the agent got a CSAT score of five Now that is super interesting because that means that customer was that agent was able to get that customer to pivot, right, from being frustrated to being happy.

So some really unique ways that people are using this as an additional data point, not just for routing, but even managing their agent expectations.

Love it. Alright. Well, let’s continue. Let’s go to step three interaction that gets back to you. Alright. So now we’ve gotten to the agent, right? And here’s the thing.

There’s this whole conversation wherever AI gets brought into the discussion.

I think people automatically assume that, you know, human beings are all gonna be put out of work. And if we’re all gonna just, I guess, sit at home and watch It’s because we’ve been watching Terminator movies to to to, you know, that’s the way it works. The human the human the human agent is not going anywhere in, in the contact center space and we’ve been talking about it for, for a number of years. But how do we make them more effective more capable when they are in that, right?

Because they are going to end up, right? If you just look at this flow, they’re gonna end up with more complex situations. Right? If you go back to my airline example, I’m not gonna contact the airline for a round trip flight, but I’m gonna contact them when there’s a storm.

Or I’m gonna contact them when I wanna do a fifty, you know, city tour or whatever it is. Right? So now they really need to be equipped to deliver that amazing experience in the shortest time as possible.

Right? And the expectations are high. Right?

I think seventy-seven is probably on the lower end because people are like, look, I tried to figure this out on my, by myself. I couldn’t. So now when they get to that agent, that agent’s gotta be rock solid. Yeah. It does feel like even that seventy-seven percent, maybe it is a hundred and five percent when I call in, you know.

And not only that, but also, you know, as this statistic shows, you know, when you get there, you also wanna be treated as an individual. Right? You don’t, you know, with the joke is nobody wants to go through the entire IVR tree again. If you’re doing that, then you’re you fail at this stage.

Right? I mean, you know, the maturity model, most people now, at least the agent is equipped to know who you are time they get to him. But more importantly, now we want the agent to be able to have a personal discussion, with this particular individual. So The challenges we see are, you know, I joke that, you know, even after twenty years of investing in technology, You still walk the floor of a contact center.

You see multiple screens.

On multiple screens, you see multiple applications, post-it notes, etcetera. So really challenging technology environment for an agent to work from. In fact, we’ve probably just piled more onto their plate you know, over the over the course of the last few years. So they’ve got these challenging tools in environments.

You know, the training is not as effective. So we’re asking them either, you know, the way I look at it deliver Zappos level of experience in as short as time as possible, and we’re gonna give you crappy tools to do it. So we might as well tell these people when you start out in the morning, you are going to fail and nobody wants to be told that, right? That’d be really difficult job. So PJ and his team have been really hard at work to really make, you know, the agent experience in life.

Better. So appreciate it. Take it away.

Sure. So the the one that we obviously said that I think the best known for is the timeline. And so questions from customers oftentimes, as I said before, in many cases, over seventy percent of customer questions that reach human beings are about the products and services that that company, has with that customer. So if you go to the next slide, Gabe, being able to see that data, instead of having to ask you, well, your order number and open up a new tab so the order management system or ask for your email and whatnot, that are, you know, the data that we store in our product So you can see not only the question that somebody’s asking, but right underneath them, say, like, the order or the product.

Or, again, whatever it is your that your business provides, be able to see that contextually. So you spend less time going back and forth, like Vicus is referring to. And then also taking actions inside of this, if we’re building out ways to make it easier on managers to try to add buttons and allow you to maybe do, like, a reset password or refunds or whatever that is all from this UI. If you go to the next slide here.

This is something that’s gonna be dropping soon specifically for if you use Shopify or some of those tools, that’s the first cost that we’re rolling out here. Again, minimize tabbing. So allow you to those agents to not have to open up all this stuff and all these different tabs, you can take action to solve problems all in one interface without having to wait for, say, like, that agent to open up that internal admin tool that the engineering team made in their spare time that’s that goes down every five minutes.

So these are these are key things that, again, from an efficiency standpoint enable agents to be able to drive better bet better engagement and more efficient, support experiences for those end customers. You go to the next slide And then additionally, this is a feature that’s in beta right now. We’re we’re hoping to release this, sometime this quarter. Is suggesting actions to agents’ next best actions and what they should be doing is oftentimes what it’s tall called, shortcuts are what we call them. Suggesting those, based on similar actions that has solved other customers’ questions that gave them a high satisfaction. That’s a bit of a mouthful, but let me put this back, say this back. If we know that we’ve delivered quality support experiences in the past for customers.

Say, like, a couple five out of five CSAT ratings, which we do know because we store that data. And we know what actions led to those solutions or to to those high c sets What we do is we actually take the question that that customer initially asked, and we can build these models based off of what those questions that customers asked are and what the solution was, what was the shortcuts that that person applied that resulted in a perfect five? Add all those things up that creates a machine learning model, which Now when somebody contacts you, we can show the agent. Okay. Well, here what we think are some actions that other agents have used in the past that resulted in perfect CSAT scores. So that that’s that’s we’re we’re still tweaking this right now going a lot with some existing customers hopefully going live later this quarter.

Love it. Alright. Alright. Last but not least, let’s let’s finalize this with kinda some of the foundational elements that you need in order to kinda get this whole machine working because.

Yeah. Look, AI is a very powerful technology. Right? And it’s all but the key thing for people to recognize, it’s only as good as your data.

Right? And if you’re if the data that you feed the pot and the best way to kind of imagine it to just, you know, for simplicity, think of it as a robot. If you had a robot in your house and, some people have this tool called the Roomba. Right?

And it and it vacuums your house. And if you only put it in one room of your house and trained it on that one room, then you let it loose on the rest of your house. It would probably knock over a bunch of things. Right?

So the data that you give, your artificial intelligence program is absolutely critical. And that’s why we look at it being part, you know, I think somebody asked the question earlier. Like, how does it compare to other tools? There are a lot of tools out there in this space.

But the key thing for us is it being part of our foundation, that foundation that has your customer, information, your order information, and building the intelligence around that so that when you do self-serve, when you do the route, when you do offer up a suggestion to your agent, it’s built off of that strong foundation of intelligence about your customers and how you’re engaging them. Yeah. And you’re seeing just a couple of stats here as we flash them.

Do you feel like this is often missed, Vicus, just before we kinda go into this? I mean, the CRM component or the data component, that’s also a little bit of a buzzword, but, is it because we’ve been so focused on just kinda solving tickets and getting tickets that we’ve kind of lost the idea of data. Why have we a lot of organizations just not gone here? Do you think?

I think it goes to, you know, everybody’s in a rush.

You know, we said from the onset, right? Everybody’s going to invest in this, you know, over a hundred percent, you know, one hundred forty percent growth. Everybody’s gonna do this.

The challenge is going to be, you know, just look at, let’s say a chat program chat deflection program that somebody sets up in terms of serving up content.

If PJ is a multimillion-a-year customer with you, and I bought, you know, one thing for a hundred dollars. And we both come to your chat window, and we ask the same question.

It doesn’t mean you wanna offer up the same solution.

Right? So having that intelligence, not only about what solution works, but what solution works for particular types of customers. If you don’t have the foundation, if you don’t have that identifier and that sense of who PJ is versus who Vicus is, it becomes very difficult to really deliver that personal element of automation and intelligence to that individual customer. Because at the end of the day, even though we may be talking to a robot, we’re not robots.

TJ, what how do you think about come, you know, using this from a solution standpoint?

Yeah.

So we’ve already kind of touched upon a lot of the other applications like deflection and now enabling agents to provide better support in which having this CRM, data is gonna enable support to be better Yeah. The thing that I’d add that we didn’t really discuss is that, you know, many businesses traditionally wait until customers contact them. Right? You use a ticketing system because the tickets are inbound questions only from the percentage of your customers that contact your business. Right? That’s the traditional model. But That doesn’t mean you couldn’t potentially wanna proactively reach out to certain customers based on maybe issues with their products or services.

So but you can’t and other tools. Right? You couldn’t do that because you’ve only the ticketing system only knows who’s contacted you. Right? So by having a system of record of not only all of your customers, but all of your customers in which products and services those customers have and allowing you to segment those customers and see information, there’s a whole level of trust and communication that your brand can build with your customers, where you can do things like proactive messaging to those individuals or as Brad or as Vicus mentioned that segmentation based off of, what products they have or lifetime value or things like that.

So I’d just like to add it. It’s not just reacting. It’s proactive. And today’s consumers are expecting that level of support.

And as the metrics show, it’s all about, you know, being able to, in my mind, differentiate not only from a product and brand standpoint, but also from a service standpoint in order to retain and grow your customer base. Yeah. I think that’s super important. Right?

That’s one of the most often missed elements. We think customer service is always gonna be inbound, but Hey, what about the outbound proactiveness that I think a lot of people are expecting these days? Yeah.

Yeah. And when people use the term CRM, I think it’s a bit it’s another one of these ubiquitous terms, nebulous. It doesn’t mean a ton, but when we think about what when we use the term CRM, it’s about being able to have all of the customers, not just the ones that contact you, and all of the data, not just tickets, things like orders or exchanges and refunds and things, communications, omnichannel communications across any messaging platform. That’s that’s really key.

Okay.

Well, guys, really appreciate your time. I know we’ve answered. Do we try to answer the questions as they came in so we won’t dive into that now. Wanda kind of just give each of you real brief.

Maybe just in summary, we hit a lot of different points, customer journey and AI and deflection and chat. Is com companies think about getting AI into their operation? What’s kinda your advice or takeaway that you would offer, Vicus will start with you, and then P. J.

Maybe we can have with you. You know, start with the journey that you’re trying to optimize, right? You know, and so what I what I would suggest to anybody, and I think I saw a question come in you know, are you guys a consulting company?

And I know why it sounds, you know, you know, a bit like that. Like we’re talking a lot about process because ultimately technology will fail if you haven’t thought through the process, right? So my recommendation to anybody is kind of map out your customer journey where do you think there are areas to optimize and then see if AI is a potential fit or solution for that optimization. And on the flip side on the agent, side as well, right?

How can you better utilize the resources you have, to handle inquiries, whether it’s the routing to route things, so maybe the way you structure your teams and your organization, or is it, hey, we’ve got that is all set up. It’s really about making our agent more impactful at the time of the interaction. So I think that’s my suggestion to anybody who’s to embark on a program. Yeah.

I think oftentimes we go for technology. For we go for kind of the shiny object, but if you don’t know what you’re solving, it’s hard to kind of find the solution. So Can’t argue that p j?

Yeah. I think I I to add on to I love what Viggas has said. Something wise. I think deflection or AI isn’t just the black box that you just turn on and solves all of your customer’s problems.

You gotta understand what your customer’s existing inquiries are to be able to know if this will even work or if what methodologies are gonna be able to solve your problem. So First, it really is is core and key to understand what are the customer questions that are coming in. And then, yes, some of those things can automatically be deflected things like articles or objects and things, but building that strategy first depends on you really understanding your customers and what your existing volume kind of like.

And and so we’re we’re right now also offering some functionality in our free tier to kinda dip dip your toes into deflection and and automation and whatnot. So we’re that’s another way. We we think we we really want the adoption of this to increase. So we put a ton of functionality into our free tier, with, you know, the hope that if it’s good and it’s enabling businesses to be successful, you’ll automatically want to be able to to use some of the more tools as as we build them out over the course of this next quarter.

I think that’s a great way to end. So if, yeah, if you are a current customer and you’re wanting to experience AI as PJ said, there is a lot of AI currently built into the platform and make sure you reach out to your customer service representative and make sure you you know that and can use it effectively. If you’re on the other side, if you’re a prospect and you’re kinda looking to get AI just into your operation, you’re seeing on the screen here. We have kind of a special offer, and we’d love to talk to you about that.

So, P. J. Vocus, thanks so much for taking the time and for the audience. Have a fantastic day.

Thanks for having us. Thanks everyone.